Top Data & Analytics Jobs

Build and maintain facility maintenance performance dashboards, monthly reports, cost-avoidance analyses, and failure/lifecycle analyses. Define metrics with government customers, validate data quality, document data sources and calculation rules, support parts-demand planning, and explain data issues to operations staff. The role requires SQL, dashboard design, data visualization, and compliance with sensitive-data and CUI handling practices.

Maintains and develops data sets, dashboards, reports, and automated ETL processes. Administers SharePoint, Teams, and assigned commercial or funder platforms; troubleshoots analytics systems; supports data security and operational improvement. Partners with agency leaders to define reporting needs, establishes data standards, provides analytics guidance, and trains users on data tools and platforms.

Analyze sales, marketing, and operational data to create dashboards, reports, predictive models, and business insights. Lead data projects, build data models and pipelines, maintain reporting accuracy, support governance and quality initiatives, and communicate findings to nontechnical stakeholders. Collaborate with leadership and cross-functional teams to improve performance, forecasting, and operational efficiency.

The Senior Data Engineer designs and maintains production data pipelines on GCP using BigQuery, Dataform, Airflow, Dataflow, and Cloud Run. They own data validation, cleansing, troubleshooting, API integrations, and reliable datasets for analytics and AI/ML. The role also involves translating client requirements into data solutions, maintaining dashboards, supporting ad hoc requests, and applying Git, code reviews, and CI/CD practices.

Manages advancement CRM systems, data integrity, fundraising and financial reporting, prospect research, donor analytics, and staff CRM support. Identifies and qualifies major-donor prospects, maintains constituent intelligence, and supports portfolio and moves management. Coordinates advancement services, alumni and donor communications, web updates, and special projects while collaborating with development leadership, gift officers, marketing, IT, and university departments.

Designs, deploys, maintains, scales, and supports enterprise database systems, primarily PostgreSQL in Linux environments. Responsibilities include database architecture, tuning, backup and recovery, failover, large-scale data management, ETL, operational support, testing with real data, and developing system features. The role also explores emerging technologies, supports customer facilities, and may contribute to cloud, DevOps, GIS, APIs, dashboards, and web development.

Provide analytic and consultative support to internal customers; translate requirements into decision-support applications; model data flows; develop complex programs and reports (SAS, R, SQL) using enterprise databases; propose and lead data-driven solutions; prepare findings and presentations for stakeholders; define data policies and security frameworks.

Builds and supports data conversion, enterprise BI, reporting, data pipelines, and warehouse integrations across legacy and modern County systems. Responsibilities include cleansing and validating data, developing Power BI dashboards and paginated reports, creating Azure Databricks and Data Factory pipelines, tuning Oracle and SQL Server solutions, modeling data with DAX/MDX, supporting Oracle financial-system integrations, documenting controls, and enabling business-user adoption.

Lead the data engineering foundation for MCG’s AI products. Build and operate data platforms, ingestion and transformation workflows, governed datasets, dashboards, and reliable production pipelines. Partner with Product, Engineering, Data Science, and customers to translate needs into technical solutions, support machine learning lifecycles, identify insights, and inform AI product decisions and roadmaps.

Design, build, and operate Databricks Lakehouse pipelines (Bronze/Silver/Gold) using Delta Lake and DLT. Optimize Spark/SQL workloads and Delta tables for performance and cost, implement incremental processing with exactly-once semantics, ensure data quality, and deliver documented datasets and dashboards (Power BI/other) with SLAs. Collaborate with cross-functional teams, integrate real-time sensor data, and support stakeholders. Occasional travel; primarily on-site.